An online digital analysis system for catalyst operation based on historical data

Abstract

The present invention relates to the technical field of digital analysis, and provides an online digital analysis system for catalyst operation based on historical data, wherein a data acquisition module acquires a large amount of historical data of a complete cycle of catalyst operation in a production catalytic reaction process and receives current catalyst operation data in real time, a data management module is communicatively connected to the data acquisition module, performs management operations on the acquired data, and a data analysis module analyzes the managed data; a performance graph display module draws a catalyst performance curve graph for the analyzed data; a performance optimization module is communicatively connected to the performance graph display module, and performs comprehensive evaluation and generates an optimization plan based on a historical performance curve graph of the catalyst and a current state performance curve graph; the present invention realizes digital analysis by drawing a catalyst performance curve graph through the performance graph display module, so that an operator can intuitively feel the change in catalyst performance, find problems in time and optimize.

Description

Technical Field

[0001] The invention relates to the technical field of digital analysis, in particular to an online digital analysis system for catalyst operation based on historical data. Background Art

[0002] In the field of chemical production, catalysts play a vital role. They can significantly accelerate the rate of chemical reactions, improve production efficiency, and reduce production costs. In addition, their performance directly affects performance indicators such as raw material consumption, energy consumption, and target product yield during the production process. The performance of catalysts directly affects the performance of the chemical production process. In traditional chemical production, the monitoring and evaluation of catalyst performance mainly rely on limited offline analysis and detection methods.

[0003] The existing background technology has the following deficiencies:

[0004] 1. In traditional chemical production, the analysis and calculation of catalyst performance mainly rely on limited offline analysis and detection methods. It is impossible to dynamically and intuitively understand the changes in catalyst performance, and it is difficult to dynamically analyze the operation of the catalyst to provide data support for system optimization, which further worsens the problem.

[0005] 2. Traditional methods do not combine multiple factors to comprehensively evaluate and optimize catalyst performance, which makes it difficult to maintain a stable output of catalyst performance during the production process, and is prone to fluctuations and uncertainties in the production process. Since the catalyst state cannot be directly reflected, the changes in the catalyst cannot be controlled in real time, and degradation and abnormalities cannot be optimized in a timely manner. Summary of the invention

[0006] The present invention provides an online digital analysis system for catalyst operation based on historical data, which dynamically analyzes the catalyst in real-time reaction based on historical data, so as to facilitate timely adjustment of the operating status of the catalyst and solve the above technical problems.

[0007] The technical solution of the present invention is as follows:

[0008] An online digital analysis system for catalyst operation based on historical data, comprising:

[0009] A data acquisition module, which is used to collect real-time data of the catalyst during the catalytic reaction process, as well as historical operation data of the catalyst. For catalysts that lack historical data, statistics can be collected through multiple catalytic reactions to obtain historical data;

[0010] A data management module, which is connected to the data collection module and performs cleaning, filtering, setting and standardization on the collected data to ensure the accuracy and availability of the data;

[0011] A data analysis module, which is data-connected to the data management module and is used to analyze the historical data of the complete operation cycle of the managed catalyst;

[0012] A performance diagram display module, which is data-connected to the data analysis module and is used to draw a catalyst performance curve diagram based on the analyzed data;

[0013] The performance optimization module is connected to the performance graph display module data, and based on the catalyst historical performance curve graph and the current performance curve graph, the current catalyst is comprehensively evaluated and optimized to achieve the best performance state.

[0014] Preferably, the historical data and real-time data of the catalyst collected by the data acquisition module include raw material flow, properties and raw material ratio data, reaction temperature, pressure, temperature rise, pressure drop, liquid level, circulation volume, auxiliary heat transfer or heat exchange system process parameters, various components of the reactor output material and process parameters of the subsequent separation section, as well as main product flow, by-product flow and tail gas volume data.

[0015] Preferably, the data governance module includes a data cleaning unit, a data filtering unit, a data setting unit and a data standardization unit;

[0016] The data cleaning unit is used to remove duplicate data, correct erroneous data and fill in missing values ​​to ensure the accuracy and completeness of the data;

[0017] The data filtering unit is used to eliminate or reduce noise and interference in the data to make the data smooth and stable;

[0018] The data setting unit is used to calibrate and adjust the data so that it conforms to the actual physical meaning and measurement standards;

[0019] The data standardization unit is used to standardize the data according to a unified format, unit and range.

[0020] Preferably, the data analysis module includes a performance calculation unit and a performance analysis unit;

[0021] The performance calculation unit is used to calculate the performance values ​​of the catalyst at different periods and working conditions according to the historical operation data of the catalyst, including stability, selectivity, and conversion rate;

[0022] The performance analysis unit is used to analyze, including but not limited to, the correlation strength of stability, selectivity, and conversion rate at different periods, different airspeeds, temperatures, and temperature fields.

[0023] Preferably, the performance calculation unit first classifies the data according to different periods and different working conditions and then performs calculations. The calculation formula is as follows:

[0024] Conversion rate calculation formula:

[0025] Selectivity calculation formula:

[0026] Historical data Catalyst stability is calculated by the mean of conversion or selectivity, with conversion or selectivity as the data point;

[0027]

[0028] Where σ is the standard deviation, the formula is μ is the mean conversion rate or selectivity, and the formula is b is the label of the data point, representing the bth data point, l b represents the value of data point b, and a represents the number of data points;

[0029] Real-time data catalyst stability measures stability by the difference between a single performance value and the average performance value;

[0030]

[0031] Where γ is the conversion rate or selectivity of the current real-time data.

[0032] Preferably, the performance analysis unit divides the historical operation data of the treated catalyst into four groups according to different periods, namely activation, initial period, middle period and final period, combined with the calculation results of the performance calculation unit;

[0033] Each set of data is calculated independently to construct a node network. The network is divided into two types of nodes, one of which is for different working conditions; the other is the performance index of the catalyst;

[0034] Let i be the label of the factor node and j be the label of the performance index node, representing the i-th factor node and the j-th performance index node, e ij is an edge, indicating the edge connecting nodes i and j; p indicates the value on the factor node, q indicates the value on the performance index node, p i is the specific value on the i node, q j is the specific value on node j;

[0035] By calculating the edge e ij The weight w ij To represent the strength of association between nodes, use the Pearson correlation coefficient:

[0036]

[0037] Among them, k is the label of the edge, p k and q k is the corresponding value of the two nodes connecting the kth edge, and are the means on the factor nodes and the performance index nodes, respectively, and r is the total number of edges;

[0038]

[0039]

[0040] Where n is the total number of factor nodes, and m is the total number of performance index nodes;

[0041] Then the topological structure and characteristics of the node network are analyzed, and the intrinsic relationship between the catalyst performance at different periods and various operating conditions is analyzed;

[0042] Clustering coefficient C i : Measures the degree of interconnection between nodes;

[0043]

[0044] Among them, F i It is the number of edges that actually exist between adjacent nodes i. The clustering coefficient reflects the degree of interconnection between nodes around a specified node. The higher the clustering coefficient, the stronger the interaction and dependence between the catalyst performance in a certain period and the performance in the adjacent period.

[0045] Preferably, the performance graph display module includes a two-dimensional graph unit and a three-dimensional graph unit;

[0046] The two-dimensional curve graph unit draws the data according to the classification results and calculation results of the performance calculation unit according to the period and different working conditions, including the conversion rate, stability and selectivity curve graphs under the conditions of use time, temperature and air speed;

[0047] The three-dimensional curve graph unit draws a three-dimensional curve graph according to the weights of the nodes and connected edges of the node network in the performance analysis unit, and constructs a curve graph that accurately reflects the change in the correlation strength between the catalyst performance and the working conditions and periods;

[0048] Node i is used as the x-axis, node j is used as the y-axis, and w ij As the z-axis; in three-dimensional space, the i-node, j-node and w-node of each period ij As three-dimensional coordinates, a space point is formed, and by connecting these space points, a three-dimensional curve graph is obtained;

[0049] At the same time, the results of data analysis are presented, and the specific values ​​of clustering coefficient indicators of different nodes are listed in a table. In the drawn graph, the meaning of the coordinate axis and the meaning of the curve are clearly marked;

[0050] Finally, the performance diagram display module marks the current state; when marking the current state, a striking color or icon is used to highlight the current catalyst performance state diagram.

[0051] Preferably, the performance optimization module includes an evaluation unit and an optimization unit;

[0052] The evaluation unit can calculate the performance difference between the current state and the similar working conditions in the historical data in real time, and the calculation formula is:

[0053]

[0054] Combined with performance differences and market conditions, the economic benefits of the catalyst under the current state are comprehensively evaluated, and a detailed evaluation report is generated, including the specific values ​​of each indicator, comparative analysis with the historical optimal state, and possible risk warnings;

[0055] When the performance difference is calculated as a positive value, the optimization unit generates an optimization plan based on the historical catalyst performance diagram to make the catalyst performance reach the optimal state; when the current performance difference is calculated as a negative value, the current catalyst performance state diagram is recorded as a more optimal state. The optimization results can be output in a variety of forms including web pages, mobile push and email.

[0056] Compared with the prior art, the present invention has the following beneficial effects:

[0057] 1. The present invention calculates the historical performance and real-time performance of the catalyst through the data analysis module and the performance graph display module, and draws an intuitive catalyst performance curve. It can dynamically and intuitively feel the changes in catalyst performance, dynamically analyze the operation of the catalyst, provide data support for subsequent optimization, ensure the stable and continuous output of catalyst performance and long-term operation, and timely discover and optimize potential problems and anomalies to avoid further deterioration.

[0058] 2. The present invention uses the system's performance optimization module to combine various factors to comprehensively evaluate the performance of the catalyst and provide improvements and optimizations, which helps to maintain the stable output of the catalyst's performance and reduce fluctuations and uncertainties in the production process. The intuitive reaction catalyst state can control the changes in the catalyst in real time, and can also generate optimization plans for degradation and abnormalities. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] Figure 1 It is a work flow chart of the present invention;

[0060] Figure 2 It is an analysis flow chart of the performance analysis unit of the present invention. DETAILED DESCRIPTION

[0061] The following embodiments of the present invention are described in further detail in conjunction with the accompanying drawings and examples. The following examples are used to illustrate the present invention, but are not intended to limit the scope of the present invention.

[0062] The present invention provides an online digital analysis system for catalyst operation based on historical data, comprising:

[0063] A data acquisition module, which is used to collect historical data of the complete operation cycle of the catalyst during the production catalytic reaction;

[0064] A data management module, which is connected to the data collection module and performs cleaning, filtering, setting and standardization on the collected data to ensure the accuracy and availability of the data;

[0065] A data analysis module, which is data-connected to the data management module and is used to analyze the historical data of the complete operation cycle of the managed catalyst;

[0066] A performance diagram display module, which is data-connected to the data analysis module and is used to draw a catalyst performance curve diagram based on the analyzed data;

[0067] The performance optimization module is connected to the performance graph display module data, and based on the catalyst historical performance curve graph and the current performance curve graph, the current catalyst is comprehensively evaluated and optimized to achieve the best performance state.

[0068] Embodiment 1: Figure 1-2 As shown, in this embodiment, with a certain catalyst, including but not limited to industrial catalyst, platinum catalyst, nickel catalyst, vanadium catalyst and biological catalyst catalase, urease, nitrogenase, etc., the operation process of the system is as follows.

[0069] First, the data acquisition module collects historical and real-time data of the catalyst, including raw material flow, properties and ratio data of each raw material, reaction temperature, pressure, temperature rise, pressure drop, liquid level, circulation volume, auxiliary heat transfer or heat exchange system process parameters, various components of the reactor output material and process parameters of the subsequent separation section, as well as main product flow, by-product flow and tail gas volume data.

[0070] The data management module performs cleaning, filtering, adjustment and standardization management operations on the collected data to ensure the accuracy and availability of the data;

[0071] The data cleaning unit removes duplicate data and corrects erroneous data, such as setting a reasonable range. For numerical data, the reasonable value range of each data field is determined based on business knowledge to ensure the accuracy and completeness of the data;

[0072] The data filtering unit eliminates or reduces noise and interference in the data to make the data smooth and stable;

[0073] The data setting unit calibrates and adjusts the data to make it conform to the actual physical meaning and measurement standards;

[0074] The data standardization unit is used to standardize data according to a unified format, unit and range.

[0075] After the treatment is completed, the data analysis module analyzes the historical data of the complete operation cycle of the treated catalyst; the data analysis module includes a performance calculation unit and a performance analysis unit.

[0076] The performance calculation unit is used to calculate the performance values ​​of the catalyst in different periods and working conditions according to the historical operation data of the catalyst, including stability, selectivity, and conversion rate.

[0077] The performance calculation unit first classifies the data according to different periods and different working conditions and then calculates them; the amount of reaction substances and input substances collected by the data acquisition module at different historical periods and working conditions are as follows:

[0078] Activation period: Amount of reacted substance: 10 mol, Amount of input substance: 50 mol

[0079] Initial stage: amount of reactant: 20 mol, amount of input: 60 mol

[0080] Mid-term: Amount of reacted substance: 30 mol, Amount of input substance: 80 mol

[0081] Final stage: amount of reacted substance: 15 mol, amount of input substance: 70 mol

[0082] The amount of substance that generates the target product is as follows:

[0083] Activation period: 5 mol, initial stage: 8 mol, mid-stage: 12 mol, final stage: 6 mol

[0084] Conversion rate calculation formula:

[0085] The amount of reacted substance refers to the amount of substance actually converted during the reaction, and the amount of input substance refers to the amount of substance initially input into the reaction system.

[0086] Selectivity calculation formula:

[0087] The amount of a substance that generates a target product refers to the amount of a substance that ultimately generates a desired product.

[0088] period Conversion rate (%) Selectivity (%) Activation period 20 50 Early stage 33.33 40 Mid-term 37.5 40 Final stage 21.43 40

[0089] Historical data Catalyst stability is calculated by the mean of conversion or selectivity, with conversion or selectivity as the data point;

[0090]

[0091] Where σ is the standard deviation, the formula is μ is the mean conversion rate or selectivity, and the formula is b is the label of the data point, representing the bth data point, l b represents the value of data point b, and a represents the number of data points;

[0092] Real-time data catalyst stability measures stability by the difference between a single performance value and the average performance value;

[0093]

[0094] Where γ is the conversion rate or selectivity of the current real-time data.

[0095] The performance analysis unit is used to analyze the correlation strength of stability, selectivity and conversion rate under different periods, different space velocities, temperatures and temperature fields. The performance analysis unit divides the historical operation data of the treated catalyst into 4 groups according to different periods, namely activation, initial stage, middle stage and final stage, and combines the calculation results of the performance calculation unit.

[0096] Each set of data is calculated independently to construct a node network. The network is divided into two types of nodes, one of which is for different working conditions; the other is the performance index of the catalyst;

[0097] Let i be the label of the factor node and j be the label of the performance index node, representing the i-th factor node and the j-th performance index node, e ij is an edge, indicating the edge connecting nodes i and j; p indicates the value on the factor node, q indicates the value on the performance index node, p i is the specific value on the i node, q j is the specific value on node j;

[0098] By calculating the edge e ij The weight w ij To represent the strength of association between nodes, use the Pearson correlation coefficient:

[0099]

[0100] Among them, k is the label of the edge, p k and q k is the corresponding value of the two nodes connecting the kth edge, and are the means on the factor nodes and the performance index nodes, respectively, and r is the total number of edges;

[0101]

[0102]

[0103] Where n is the total number of factor nodes, and m is the total number of performance index nodes;

[0104] Then the topological structure and characteristics of the node network are analyzed, and the intrinsic relationship between the catalyst performance at different periods and various operating conditions is analyzed;

[0105] Clustering coefficient C i : Measures the degree of interconnection between nodes;

[0106]

[0107] Among them, F i It is the number of edges that actually exist between adjacent nodes i. The clustering coefficient reflects the degree of interconnection between nodes around a specified node. The higher the clustering coefficient, the stronger the interaction and dependence between the catalyst performance in a certain period and the performance in the adjacent period.

[0108] The division of data groups in the performance analysis unit can also be divided into the following groups:

[0109] The performance calculation unit classifies and calculates the data, accurately obtains key performance indicators such as conversion rate and selectivity at different times, and provides a reliable data basis for subsequent performance analysis. At the same time, quantitatively evaluate the stability of the catalyst under different conditions, which is crucial to ensure the efficient operation of the catalyst and the stability of the production process;

[0110] By building a node network and calculating indicators such as edge weights and clustering coefficients, the intrinsic relationship between catalyst performance and various working conditions is revealed, providing a scientific basis for optimizing the use of catalysts and production processes. The optimal use stage and life cycle of catalysts can be determined; by studying the correlation strength between performance index and working conditions, process parameters can be adjusted in real time to improve catalyst performance and stability, and provide a reference basis for future catalyst reactions, ensuring the efficient operation of catalytic reactions.

[0111] It comprehensively considers the impact of multiple factors on catalyst performance, and can provide comprehensive and accurate performance evaluation and optimization suggestions through precise calculations and in-depth analysis. Compared with traditional analysis methods, it provides a new analysis perspective and method that is more scientific and efficient, and can bring greater value to users.

[0112] The performance graph display module includes a two-dimensional graph unit and a three-dimensional graph unit, and uses MATLAB and other software to draw graphs;

[0113] The two-dimensional curve chart unit draws the data according to the classification results and calculation results of the performance calculation unit according to the period and different working conditions, including the conversion rate, stability and selectivity curves under the conditions of use time, temperature and air speed;

[0114] The three-dimensional curve graph unit draws a three-dimensional curve graph according to the weights of the nodes and connected edges of the node network in the performance analysis unit, and constructs a curve graph that accurately reflects the change in the correlation strength between the catalyst performance and the working conditions and periods;

[0115] Node i is used as the x-axis, node j is used as the y-axis, and w ij As the z-axis; in three-dimensional space, the i-node, j-node and w-node of each period ij As three-dimensional coordinates, a space point is formed, and by connecting these space points, a three-dimensional curve graph is obtained;

[0116] At the same time, the results of data analysis are presented, and the specific values ​​of clustering coefficient indicators of different nodes are listed in a table. In the drawn graph, the meaning of the coordinate axis and the meaning of the curve are clearly marked;

[0117] Finally, the performance diagram display module marks the current state; when marking the current state, a striking color or icon is used to highlight the current catalyst performance state diagram.

[0118] The performance optimization module includes an evaluation unit and an optimization unit;

[0119] The evaluation unit can calculate the performance difference between the current state and similar working conditions in historical data in real time. The calculation formula is:

[0120]

[0121] Combined with performance differences and market conditions, the economic benefits of the catalyst under the current state are comprehensively evaluated, and a detailed evaluation report is generated, including the specific values ​​of each indicator, comparative analysis with the historical optimal state, and possible risk warnings;

[0122] When the performance difference is calculated as a positive value, the optimization unit generates an optimization plan based on the historical catalyst performance diagram to make the catalyst performance reach the optimal state; when the current performance difference is calculated as a negative value, the current catalyst performance state diagram is recorded as a better state. The optimization results can be output in a variety of forms including web pages, mobile push and email.

[0123] The system's performance optimization module combines various factors to comprehensively evaluate the performance of the catalyst and provide improvements and optimizations, which helps maintain the stable output of the catalyst's performance and reduce fluctuations and uncertainties in the production process. The intuitive reaction catalyst status provides real-time control of the catalyst's changes and can generate optimization plans for degradation and abnormalities.

[0124] Embodiment 2: Figure 1-2 As shown, in this embodiment, in the process of performance analysis unit calculation in the first embodiment, weight calculation can also be performed in multiple groups;

[0125] For example, the historical operating data of the catalyst after treatment can be grouped according to different working conditions and combined with the calculation results of the performance calculation unit; each group of data is calculated independently to build a node network. The network is divided into two types of nodes, one for different periods and the other for the performance index of the catalyst. Through this grouping, the weight between the period node and the performance index node can be calculated, thereby analyzing the degree of correlation between different periods and the performance index.

[0126] By performing weight-related calculations on different groups, more analytical perspectives are provided, which is more conducive to subsequent optimization and provides strong support for realizing various optimization schemes in the real-time reaction of catalysts.

[0127] The embodiments of the present invention are provided for the purpose of illustration and description. Although the embodiments of the present invention have been shown and described above, it can be understood that the above embodiments are exemplary and cannot be understood as limitations of the present invention. Ordinary technicians in this field can change, modify, replace and modify the above embodiments within the scope of the present invention.

Claims

1. An online digital analysis system for catalyst operation based on historical data, characterized in that: include: A data acquisition module, which is used to collect real-time data of the catalyst during the catalytic reaction process, as well as historical operation data of the catalyst. For catalysts that lack historical data, statistics can be collected through multiple catalytic reactions to obtain historical data; A data management module, which is connected to the data collection module and performs cleaning, filtering, setting and standardization on the collected data to ensure the accuracy and availability of the data; A data analysis module, which is data-connected to the data management module and is used to analyze the managed catalyst data; A performance diagram display module, which is data-connected to the data analysis module and is used to draw a catalyst performance curve diagram based on the analyzed data; A performance optimization module, which is data-connected to the performance graph display module, performs a comprehensive evaluation of the current catalyst and provides an optimization plan based on the catalyst's historical performance curve graph and the current performance curve graph; The data analysis module includes a performance calculation unit and a performance analysis unit; The performance calculation unit is used to calculate the performance values ​​of the catalyst at different periods and working conditions according to the historical operation data of the catalyst, including stability, selectivity, and conversion rate; The performance analysis unit is used to analyze the correlation strength of stability, selectivity and conversion rate at different periods, different airspeeds, temperatures and temperature fields; The performance analysis unit divides the historical operation data of the treated catalyst into four groups according to different periods, namely activation, initial period, middle period and final period, and combines the calculation results of the performance calculation unit; Each set of data is calculated independently to construct a node network. The network is divided into two types of nodes, one of which is for different working conditions; the other is the performance index of the catalyst; Let i be the label of the factor node and j be the label of the performance index node, representing the i-th factor node and the j-th performance index node. is an edge, indicating the edge connecting nodes i and j; represents the value on the factor node, represents the value on the performance index node, is the specific value on the i node, is the specific value on node j; By calculating the edge Weight To represent the strength of association between nodes, use the Pearson correlation coefficient: ； Where k is the label of the edge, and is the corresponding value of the two nodes connecting the kth edge, and are the means on the factor nodes and the performance index nodes, respectively, and r is the total number of edges; ； Where n is the total number of factor nodes, and m is the total number of performance index nodes; Then the topological structure and characteristics of the node network are analyzed, and the intrinsic relationship between the catalyst performance at different periods and various operating conditions is analyzed; Clustering coefficient : Measures the degree of interconnection between nodes; ； in, It is the number of edges that actually exist between adjacent nodes i. The clustering coefficient reflects the degree of interconnection between nodes around a specified node. The higher the clustering coefficient, the stronger the interaction and dependence between the catalyst performance in a certain period and the performance in the adjacent period.

2. The catalyst operation online digital analysis system based on historical data as claimed in claim 1, characterized in that: The data acquisition module collects historical and real-time data of the catalyst, including raw material flow, properties and raw material ratio data, reaction temperature, pressure, temperature rise, pressure drop, liquid level, circulation volume, auxiliary heat transfer or heat exchange system process parameters, various components of reactor output materials and process parameters of subsequent separation sections, as well as main product flow, by-product flow and tail gas volume data.

3. The catalyst operation online digital analysis system based on historical data as claimed in claim 1, characterized in that: The data governance module includes a data cleaning unit, a data filtering unit, a data setting unit and a data standardization unit; The data cleaning unit is used to remove duplicate data, correct erroneous data and fill in missing values ​​to ensure the accuracy and completeness of the data; The data filtering unit is used to eliminate or reduce noise and interference in the data to make the data smooth and stable; The data setting unit is used to calibrate and adjust the data so that it conforms to the actual physical meaning and measurement standards; The data standardization unit is used to standardize the data according to a unified format, unit and range.

4. The catalyst operation online digital analysis system based on historical data as claimed in claim 1, characterized in that: The performance calculation unit first classifies the data according to different periods and different working conditions and then performs calculations. The calculation formula is as follows: ； Historical data Catalyst stability is calculated by the mean of conversion or selectivity, with conversion or selectivity as the data point; ； in, is the standard deviation, and the formula is , is the mean conversion rate or selectivity, and the formula is , b is the label of the data point, representing the bth data point, represents the value of data point b, Indicates the number of data points; Real-time data catalyst stability measures stability by the difference between a single performance value and the average performance value; ； in, It is the conversion rate or selectivity of the current real-time data.

5. The catalyst operation online digital analysis system based on historical data as claimed in claim 1, characterized in that: The performance graph display module includes a two-dimensional graph unit and a three-dimensional graph unit; The two-dimensional curve graph unit draws the data according to the classification results and calculation results of the performance calculation unit according to the period and different working conditions, including the conversion rate, stability and selectivity curve graphs under the conditions of use time, temperature and air speed; The three-dimensional curve graph unit draws a three-dimensional curve graph according to the weights of the nodes and connected edges of the node network in the performance analysis unit, and constructs a curve graph that accurately reflects the change in the correlation strength between the catalyst performance and the working conditions and periods; With node i as the x-axis and node j as the y-axis, as the z-axis; In three-dimensional space, the i nodes, j nodes and are three-dimensional coordinates, forming a spatial point, and by connecting these spatial points, a three-dimensional curve graph is obtained; At the same time, the results of data analysis are presented, and the specific values ​​of clustering coefficient indicators of different nodes are listed in a table. In the drawn graph, the meaning of the coordinate axis and the meaning of the curve are clearly marked; Finally, the performance diagram display module marks the current state; when marking the current state, a striking color or icon is used to highlight the current catalyst performance state diagram.

6. The catalyst operation online digital analysis system based on historical data as claimed in claim 1, characterized in that: The performance optimization module includes an evaluation unit and an optimization unit; The evaluation unit can calculate the performance difference between the current state and the similar working conditions in the historical data in real time, and the calculation formula is: ； Combined with performance differences and market conditions, the economic benefits of the catalyst under the current state are comprehensively evaluated, and a detailed evaluation report is generated, including the specific values ​​of each indicator, comparative analysis with the historical optimal state, and possible risk warnings; When the performance difference is calculated as a positive value, the optimization unit generates an optimization plan according to the historical catalyst performance map to make the catalyst performance reach the optimal state; When the current performance difference is calculated as a negative value, the current catalyst performance status diagram is recorded as a better state. The optimization results can be output in a variety of forms including web pages, mobile push and email.

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